Automated and real-time segmentation of suspicious breast masses using convolutional neural network.
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ABSTRACT:
SUBMITTER: Kumar V
PROVIDER: S-EPMC5955504 | biostudies-literature | 2018
REPOSITORIES: biostudies-literature
Publications
Automated and real-time segmentation of suspicious breast masses using convolutional neural network.
Kumar Viksit V Webb Jeremy M JM Gregory Adriana A Denis Max M Meixner Duane D DD Bayat Mahdi M Whaley Dana H DH Fatemi Mostafa M Alizad Azra A
PloS one 20180516 5
In this work, a computer-aided tool for detection was developed to segment breast masses from clinical ultrasound (US) scans. The underlying Multi U-net algorithm is based on convolutional neural networks. Under the Mayo Clinic Institutional Review Board protocol, a prospective study of the automatic segmentation of suspicious breast masses was performed. The cohort consisted of 258 female patients who were clinically identified with suspicious breast masses and underwent clinical US scan and br ...[more]
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